How cross-industry data collaboration powers innovation

Blog: Capgemini CTO Blog

This article first appeared on Capgemini’s Data-powered Innovation Review | Wave 3.

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Innovation doesn’t happen in a vacuum. The development of new products, services, and solutions involves input and information from a multitude of sources. Increasingly, many of these sources are not only beyond an organization’s borders but also beyond the organization’s industry. According to a 2020 research paper on cross sector partnerships, “Cross-industry

innovation is becoming more relevant for firms, as this approach often results in radical innovations.” But developing innovations through cross-industry partnerships must involve coordinated data collaboration. “Firms can only benefit from cross-industry innovation if they are open to external knowledge sources and understand how to explore, transform, and exploit cross-industry knowledge,” the paper’s authors noted. “Firms must establish certain structures and processes to facilitate and operationalize organizational learning across industry boundaries.”

“WE’VE SEEN AN INCREASE IN THE NUMBER OF CUSTOMERS WHO WANT TO COLLABORATE ON DATA FROM OTHER INDUSTRIES TO SPUR NEW IDEAS.”

Examples of cross-industry data collaboration

There is a multitude of examples of how organizations across industries have spurred innovation through collaboration.

In financial services, institutions that must prevent and detect fraud use cross-industry data sharing to better understand the profile of fraudsters and fraudulent transaction patterns.
In manufacturing, companies are using AI to manage supply-chain disruptions. Using data from external sources on weather, strikes, civil unrest, and other factors, they can acquire a full view of supply-chain issues to mitigate risks early.
In energy, smart meters in individual homes open new doors for data collaboration, transmitting information about energy consumption.
In education, school systems, local governments, businesses, and community organizations work together to improve educational outcomes for students.
In healthcare, during the COVID-19 pandemic, hospitals relied on information from health agencies and drug companies regarding the progression and transmission behavior of diseases. Governments followed data from scientists and healthcare professionals to create guidance for the public. Retailers heeded guidance from the public and healthcare sectors to create new in-store policies and shift much of their business online.

The role of cross-industry data collaboration in innovation during the pandemic is perhaps nowhere better exemplified than in the COVID-19 Research Database, involving a cross-industry consortium of organizations. The database, which can be accessed by academic, scientific, and medical researchers, holds billions of de-identified records including unique patient claims data, electronic health records, and mortality data. This has enabled academic researchers in medical and scientific fields as well as public health and policy researchers to use real-world data to combat the COVID-19 pandemic in novel ways.

Best practices for cross-industry collaboration

As the examples above show, organizations that have developed cross-industry data collaboration capabilities can more easily foster innovation, leading to a competitive advantage. Here are some of the considerations and best practices that enable sharing and collaborating on knowledge across industries.

A single, governed source for all data:
Each industry – and indeed, each company – stores and formats its data in different ways and places. Housing data in one governed location makes it easier to gather, organize, and share semi-structured and structured data easily and securely.

Simplified data sharing:
The relevant data must be easily accessible and shareable by all partners. Data is stored in different formats and types, and it can be structured, semi-structured, or unstructured. It can be siloed in specific departments and difficult or slow to move, or inaccessible to the outside world. What processes and tools are in place to transform cross-industry knowledge into a shareable, usable format?

Secure data sharing:
Data privacy is of the utmost importance in today’s society. Data must be shareable securely and in compliance with privacy regulations. Cross-industry data sharing often involves copying and moving data, which immediately opens up security risks. There may also be different data protection and privacy regulations in different industries.

Inexpensive data management:
Data must be shareable, and budgets kept in mind. Centralizing, organizing, securing, and sharing data is often resource-intensive, so organizations need to find ways to manage and share their data more efficiently.

Democratized data:
While data security and privacy are paramount, companies must “democratize” data so that it is accessible and shareable in a way that allows non-technical users in both internal and external parties to use it easily.

Advanced analytics:
Technologies such as AI and machine learning can help companies glean deeper insights from data. This requires a data foundation and tools that can analyze all types of data. Technological tools are making it easier for organizations to follow and gain ROI from these best practices.

For example, Snowflake’s Data Cloud enables the seamless mobilization of data across public clouds and regions, empowering organizations to share live, governed, structured, semistructured, and unstructured data (in public preview) externally without the need for copying or moving. Snowflake enables compliance with government and industry regulations, and organizations can store near-unlimited amounts of data and process it with exceptional performance using a “pay only for what you use” model. They can also use Snowflake’s robust partner ecosystem to analyze the data for deeper insights and augment their analysis with external data sets.

“We’ve seen an increase in the number of customers who want to collaborate on data from other industries to spur new ideas,” Snowflake’s Co-Founder and President of Products Benoit Dageville said, “ to foster innovation, to be able to freely collaborate within and outside of their organization, without added complexity or cost.”

The future of mass collaboration In the future, cross-sector data collaboration will only play a larger role in innovation as technology becomes more ubiquitous and the public grows more comfortable with sharing data. We could see worldwide consortiums that collaborate on data to solve some of humanity’s biggest problems: utilizing medical and scientific information to tackle global health crises, enabling more-efficient use of resources to fight poverty and climate change, and combating misinformation.

Organizations such as the World Bank are already working on such initiatives. Its Data Innovation Fund is working to help countries benefit from new tools and approaches to produce, manage, and use data. According to a recent World Bank blog post, “Collaboration between private organizations and government entities is both possible and critical for data innovation. National and international organizations must adopt innovative technologies in their statistical processes to stay current and meet the challenges ahead.”

To unlock the potential of innovation through data collaboration, organizations must make sure their data management and sharing capabilities are up to date. A robust, modern data platform can go a long way. But what’s also needed is an audit of internal processes and tools to ensure that barriers to data sharing and analysis are not impeding innovation and growth.

INNOVATION TAKEAWAYS

COLLABORATION NEEDS BEST PRACTICES

Organizations that implement best practices in cross-industry data collaboration can foster innovation, leading to a competitive advantage.

DATA CAPABILITIES MUST BE UP TO DATE

Organizations must make sure their data management and sharing capabilities are current, to unlock the potential of innovation through data collaboration.

TECHNOLOGY AND PLATFORMS TO THE RESCUE

Dedicated tools and data platforms make it easier for organizations to gain cross-sector data-collaboration capabilities much quicker.

Interesting read?

Data-powered Innovation Review | Wave 3 features 15 such articles crafted by leading Capgemini experts in data, sharing their life-long experience and vision in innovation. In addition, several articles are in collaboration with key technology partners such as Google, Snowflake, Informatica, Altair, A21 Labs, and Zelros to reimagine what’s possible. Download your copy here!